Identification of an Iron-Sulfur Cluster That Modulates the Enzymatic Activity in NarE, a Neisseria meningitidis ADP-ribosyltransferase
Bibliographic record
Abstract
In prokaryotes, mono-ADP-ribose transfer enzymes represent a family of exotoxins that display activity in a variety of bacterial pathogens responsible for causing disease in plants and animals, including those affecting mankind, such as diphtheria, cholera, and whooping cough. We report here that NarE, a putative ADP-ribosylating toxin previously identified from Neisseria meningitidis, which shares structural homologies with Escherichia coli heat labile enterotoxin and toxin from Vibrio cholerae, possesses an iron-sulfur center. The recombinant protein was expressed in E. coli, and when purified at high concentration, NarE is a distinctive golden brown in color. Evidence from UV-visible spectrophotometry and EPR spectroscopy revealed characteristics consistent of an iron-binding protein. The presence of iron was determined by colorimetric method and by an atomic absorption spectrophotometer. To identify the amino acids involved in binding iron, a combination of site-directed mutagenesis and UV-visible and enzymatic assays were performed. All four cysteine residues were individually replaced by serine. Substitution of Cys(67) and Cys(128) into serine caused a drastic reduction in the E(420)/E(280) ratio, suggesting that these two residues are essential for the formation of a stable coordination. This modification led to a consistent loss in ADP-ribosyltransferase activity, while decrease in NAD-glycohydrolase activity was less dramatic in these mutants, indicating that the correct assembly of the iron-binding site is essential for transferase but not hydrolase activity. This is the first observation suggesting that a member of the ADP-ribosyltransferase family contains an Fe-S cluster implicated in catalysis. This observation may unravel novel functions exerted by this class of enzymes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".